Charging operation method, device and storage medium based on vehicle identification code

Abstract

The present application relates to the field of new energy vehicle power supply, and provides a charging operation method based on a vehicle identification code, the method comprising: establishing a binding relationship between a vehicle corresponding to the VIN and an operation platform by obtaining a vehicle identity identification code (VIN) and a license plate number input by a user, and storing the bound VIN as a user pre-stored VIN in a database of the operation platform; the operation platform generates a dynamic charging control instruction based on real-time grid load data, user charging demand, and vehicle battery parameters corresponding to the user's pre-stored VIN, and sends it to a target charging pile; when the target charging pile executes the control instruction, the battery status parameters and charging pile operation data of the vehicle's BMS are collected in real time; the battery status parameters and charging pile operation data are associated with the user's pre-stored VIN, and the charging parameters are dynamically adjusted through multi-dimensional data fusion analysis; after charging is completed, an encrypted settlement message is generated based on the charging record associated with the user's pre-stored VIN; the encrypted settlement message is stored on the chain through blockchain technology to complete the fee settlement.

Description

Technical Field

[0001] The present application relates to the field of new energy vehicle power supply, and in particular to a charging operation method, device and storage medium based on a vehicle identification code. Background Art

[0002] With the rapid development of the new energy vehicle industry, intelligent operation of charging infrastructure has become a core industry requirement. As a vehicle's unique identifier, the Vehicle Identification Number (VIN) plays a key role in vehicle identity verification, data association, and service matching in charging scenarios. Current mainstream charging operation systems typically implement services based on simple interactions between user accounts and charging stations. However, significant bottlenecks remain in grid coordination, dynamic regulation, and data security.

[0003] In the existing technology, charging pile operation systems mostly adopt the following solutions: the identity authentication link relies on single-factor verification of mobile terminals; charging instruction generation is mainly based on fixed strategies; charging process data collection and user identity information are stored separately; and the settlement process relies on centralized platform processing.

[0004] These technical shortcomings lead to the following issues: single authentication methods are vulnerable to counterfeit attacks, threatening charging safety; static command strategies struggle to balance grid load and charging efficiency; decentralized data storage structures hinder real-time control and optimization; and centralized settlement systems are susceptible to single points of failure. Therefore, a smart charging operation approach that deeply integrates vehicle identity, dynamic control, and trusted settlement is urgently needed. Summary of the Invention

[0005] The present application provides a charging operation method, device and storage medium based on a vehicle identification code, which can significantly improve charging safety, optimize efficiency and ensure cost credibility.

[0006] In one aspect, the present application provides a charging operation method based on a vehicle identification code, the method comprising:

[0007] By obtaining the vehicle identification code (VIN) and license plate number input by the user, a binding relationship between the vehicle corresponding to the VIN and the operation platform is established, and the bound VIN is stored as the user's pre-stored VIN in the database of the operation platform;

[0008] The operation platform generates dynamic charging control instructions based on real-time grid load data, user charging needs, and vehicle battery parameters corresponding to the user's pre-stored VIN and sends them to the target charging pile;

[0009] When the target charging pile executes the control instruction, the battery status parameters of the vehicle battery management system BMS and the charging pile operation data are collected in real time;

[0010] Associating the battery status parameters and charging pile operation data with the user's pre-stored VIN, and dynamically adjusting the charging parameters through multi-dimensional data fusion analysis;

[0011] After charging is completed, an encrypted settlement message is generated based on the charging record associated with the user's pre-stored VIN;

[0012] The encrypted settlement message is stored on the chain through blockchain technology, and the user is notified after the fee settlement is completed.

[0013] On the other hand, the present application provides a charging operation device based on a vehicle identification code, the device comprising:

[0014] A binding module is used to establish a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identity identification code (VIN) and license plate number input by the user, and store the bound VIN as the user's pre-stored VIN in the database of the operation platform;

[0015] The first generation module is used for the operation platform to generate dynamic charging control instructions based on real-time grid load data, user charging needs and vehicle battery parameters corresponding to the user's pre-stored VIN and send them to the target charging pile;

[0016] An acquisition module is used to collect battery status parameters and charging pile operation data of the vehicle battery management system BMS in real time when the target charging pile executes the control instruction;

[0017] An association module is used to associate the battery status parameters and charging pile operation data with the user's pre-stored VIN, and dynamically adjust the charging parameters through multi-dimensional data fusion analysis;

[0018] A second generating module is configured to generate an encrypted settlement message based on the charging record associated with the user's pre-stored VIN after charging is completed;

[0019] The evidence storage module is used to store the encrypted settlement message on the chain through blockchain technology and notify the user after the fee settlement is completed.

[0020] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the technical solution of the charging operation method based on the vehicle identification code as described above are implemented.

[0021] In a fourth aspect, the present application provides a storage medium storing a computer program, which, when executed by a processor, implements the steps of the technical solution of the above-mentioned charging operation method based on the vehicle identification code.

[0022] From the technical solutions provided in the present application, it can be seen that, on the one hand, by bidirectionally binding and verifying the VIN input by the user with the vehicle hardware information obtained in real time by the charging pile, a dual-channel authentication mechanism is constructed, which effectively prevents illegal users from accessing the charging system by forging account information, thereby fundamentally improving the security of charging operations. Control instructions are dynamically generated based on real-time grid load data, user needs, and vehicle battery parameters associated with the pre-stored VIN, so that the charging strategy can synchronously respond to changes in grid status and vehicle characteristics, breaking through the limitations of traditional fixed strategies, and enhancing grid stability while ensuring charging efficiency; on the other hand, by correlating and analyzing the real-time operating data collected by the charging pile with the pre-stored VIN, a dynamic mapping relationship of identity-status-control is established, and closed-loop optimization and adjustment of charging parameters is achieved, providing data support for solving safety hazards such as battery overheating and voltage abnormalities; thirdly, blockchain technology is used to store VIN-associated charging records on the chain, and its decentralized and tamper-proof characteristics are utilized to ensure the integrity and auditability of settlement data, effectively avoiding the data leakage and single point failure risks of traditional centralized settlement systems. In summary, the technical solution of the present application can significantly improve the charging safety of charging piles, optimize efficiency and ensure cost credibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0024] Figure 1 This is a flow chart of a charging operation method based on a vehicle identification code provided in an embodiment of the present application;

[0025] Figure 2 This is a structural diagram of a charging operation device based on a vehicle identification code provided in an embodiment of the present application;

[0026] Figure 3 It is a schematic diagram of the structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0028] In this specification, adjectives such as first and second may be used only to distinguish one element or action from another element or action, without necessarily requiring or implying any actual such relationship or order. Where circumstances permit, reference to an element or component or step (etc.) should not be construed as being limited to only one of the elements, components, or steps, but may be one or more of the elements, components, or steps, etc.

[0029] In this specification, for the convenience of description, the sizes of various parts shown in the drawings are not drawn according to the actual proportions.

[0030] As the unique identity of a car, the Vehicle Identification Number (VIN) plays a key role in vehicle identity verification, data association, and service matching in charging scenarios. The current mainstream charging operation system usually implements services based on simple interactions between user accounts and charging piles. However, there are still significant bottlenecks in grid coordination, dynamic regulation, and data security. In existing technologies, charging pile operation systems often adopt the following solutions: (1) The identity authentication link relies on single-factor authentication of mobile terminals and lacks a two-way verification mechanism at the vehicle hardware level; (2) Charging instruction generation is mainly based on fixed strategies, which makes it difficult to respond to grid load fluctuations and dynamic changes in user demand in a timely manner; (3) Charging process data collection and user identity information are separated and stored, resulting in a lack of multi-dimensional correlation analysis support for control decisions; (4) The settlement process relies on centralized platform processing, which has the risk of data tampering and insufficient fault recovery capabilities. The above-mentioned existing technical defects lead to the following problems: the single authentication method is prone to counterfeit attacks, threatening charging safety; the static instruction strategy is difficult to balance grid load and charging efficiency; the decentralized data storage structure hinders real-time control optimization; and the centralized settlement system is susceptible to single point failures. Therefore, there is an urgent need for an intelligent charging operation method that deeply integrates vehicle identity, dynamic regulation and trusted settlement.

[0031] In response to the above problems of the prior art, this application proposes a charging operation method based on vehicle identification code, the flow chart of which is shown in the attached Figure 1 As shown, it mainly includes steps S101 to S106, which are detailed as follows:

[0032] Step S101: A binding relationship between the vehicle corresponding to the VIN and the operation platform is established by obtaining the vehicle identification code VIN and license plate number input by the user, and the bound VIN is stored as the user's pre-stored VIN in the database of the operation platform.

[0033] In the prior art, charging operations for electric vehicles that rely solely on license plates are vulnerable to forged license plate attacks. Using only the Vehicle Identification Number (VIN) makes it impossible to verify the actual association between the vehicle and the user. The VIN is the vehicle's unique identifier, while the license plate number serves as auxiliary verification information. When the two are not bound together, the charging station cannot verify the vehicle's legitimacy, potentially leading to unauthorized vehicle access. Therefore, to prevent the tampering or misuse of a single identifier and provide a foundation for subsequent charging permission control and data association, in an embodiment of the present application, a binding relationship between the VIN-corresponding vehicle and the operation platform can be established by obtaining the user-entered vehicle identification code (VIN) and license plate number. Furthermore, considering that if the VIN is not pre-stored, the authenticity of the real-time VIN cannot be verified in subsequent steps of the VIN-based charging operation method, breaking the identity verification chain, the bound VIN can be stored as the user's pre-stored VIN in the operation platform's database, serving as reference data for subsequent processes, such as instruction generation, data association, and settlement evidence.

[0034] As an embodiment of the present application, establishing a binding relationship between a vehicle corresponding to the VIN and an operation platform by obtaining the vehicle identification code VIN and the license plate number input by the user can be achieved through steps S1011 to S1013, as detailed below:

[0035] Step S1011: When the charging gun of the target charging pile is inserted into the vehicle corresponding to the VIN, the VIN is obtained in real time through the interface of the vehicle battery management system BMS.

[0036] The vehicle's Battery Management System (BMS) is the core controller of the vehicle's battery. Commercial vehicle communication protocols require the BMS to support VIN query functionality. Therefore, when a charging plug from a target charging station is plugged into a vehicle with a matching VIN, a communication link is established between the target charging station and the vehicle's BMS via a physical interface (e.g., the CC / CP pins). A standardized VIN request command (e.g., the $22 service in the UDS protocol) is sent, and the BMS retrieves the VIN from the VCU and returns it.

[0037] Step S1012: When the BMS communication is abnormal, the radio frequency identification (RFID) reader is activated to scan the vehicle electronic tag to obtain the backup VIN.

[0038] If the system relies solely on the BMS interface, its robustness will be insufficient, for example, due to incompatible vehicle BMS versions. The Radio Frequency Identification (RFID) backup mechanism is a technical means to obtain a trusted VIN when the hardware interface fails. This means that when BMS communication is abnormal, the backup VIN can be obtained by activating the RFID reader to scan the vehicle's electronic tag. From steps S1011 and S1012, it can be seen that this dual-channel verification mechanism through dual-channel BMS+RFID can not only ensure service continuity in extreme scenarios, but also prevent charging permissions from being obtained by forging BMS data, which makes the system anti-fraud.

[0039] Step S1013: matching and verifying the VIN obtained in real time or the backup VIN with the user's pre-stored VIN.

[0040] Specifically, the VIN obtained in real time or the backup VIN is matched and verified with the user's pre-stored VIN as follows: the operation platform generates a dynamic verification key and divides it into a first key segment and a second key segment; sends the first key segment to the user's mobile terminal for biometric verification; transmits the second key segment to the target charging pile, and controls its display screen to generate a dynamic QR code containing the second key segment; after the user scans the dynamic QR code, the scanning result is associated with the result of the biometric verification for verification; when the verification passes and the VIN obtained in real time or the backup VIN is consistent with the user's pre-stored VIN, the matching verification of the VIN obtained in real time or the backup VIN and the user's pre-stored VIN is passed. Considering that the keys of traditional encryption algorithms are easily cracked by quantum computing, this means that if fixed keys or simple hashes are used, the high security requirements in the Internet of Vehicles scenario cannot be met. The initial value sensitivity and pseudo-randomness of the chaos algorithm can resist brute force cracking. Therefore, in the above embodiment, the operation platform generates a dynamic verification key by: generating an initial key seed based on the hash value of the user's pre-stored VIN; generating a dynamic perturbation factor based on the geographic location and real-time timestamp of the target charging pile; and finally generating a dynamic verification key by fusing the initial key seed with the dynamic perturbation factor through the chaos algorithm.

[0041] In the above embodiment, the dynamic disturbance factor generated by combining the geographic location and real-time timestamp of the target charging pile can be: encoding the geographic location of the target charging pile and normalizing it into a geographic location normalized value; segmenting the real-time timestamp according to preset rules, intercepting the following several digits as the dynamic component, intercepting the current number of seconds as the periodic component, and then dividing the sum of the dynamic component and the periodic component by a certain number, such as 10000, to obtain the timestamp disturbance component; finally, performing weighted summation on the geographic location normalized value and the timestamp disturbance component to obtain the disturbance factor and recalculating the above disturbance factor once per preset interval to dynamically update the disturbance factor. In the above embodiment, the technical solution of fusing the initial key seed with the dynamic disturbance factor through a chaotic algorithm to finally generate a dynamic verification key mainly includes initializing the chaotic system, iterating and extracting the key from the chaotic sequence, and finally generating the dynamic verification key through obfuscation means. Among them, initializing the chaotic system can be selecting a Logistic chaotic map as a chaotic model. ,in, r is the fractal parameter (usually 3.99~4.0), is the current state value (the initial value is determined by the key seed and the perturbation factor), then, the initial key seed is input into the chaotic model, the key seed is converted into decimal, the perturbation factor is combined with the decimal value of the initial key seed to generate a chaotic initial value; iterating the chaotic sequence and extracting the key includes performing a preset number of (for example, 500) warm-up iterations under the established fractal parameters and chaotic initial value to eliminate transient effects, and then continuing to iterate to generate valid sequences, converting these valid sequences into binary and splicing these binary fragments into a 256-bit original key sequence; as for the final generation of the dynamic verification key by obfuscation means, the dynamic perturbation factor can be injected twice, that is, the perturbation factor (0.835) is converted into 8-bit binary, and then, the original key sequence is XOR-ed, and finally, the first several bits (for example, 128 bits) are intercepted from the obfuscated sequence as the dynamic verification key.

[0042] The above-mentioned dynamic key generation mechanism not only increases the difficulty of cracking, but also avoids the reuse of keys by combining the geographic location of the target charging pile with the real-time timestamp, fully demonstrating the environmental adaptability of the solution.

[0043] It should be noted that the parameters of the above-mentioned chaotic algorithm can be pre-configured in the following manner: based on the parity and even bit distribution characteristics of the user's pre-stored VIN, the iteration number calculation rule is dynamically selected, that is, if the sum of the odd digits of the user's pre-stored VIN is greater than the even digits, the iteration number N = the sum of the odd digits × 2; otherwise, N = the sum of the even digits + the preset base number; based on the model code of the target charging pile, the hardware performance level is parsed and the disturbance amplitude threshold R is set according to the following rules: high-performance pile (code initials A / B): R = 0.5 × (charging pile rated power / 100), standard pile (code initials C / D): R = 0.3 × (charging pile rated power / 100); based on the iteration number N and the disturbance amplitude threshold R, the key generation time is calculated using the formula T = K × N × log (R), and the calculation accuracy of the chaotic algorithm is dynamically adjusted to ensure that the key generation time T is not greater than the preset threshold time, for example, 200ms. In the calculation formula of the key generation time T, K is the hardware performance compensation coefficient.

[0044] Step S102: The operation platform generates dynamic charging control instructions based on real-time grid load data, user charging requirements, and vehicle battery parameters corresponding to the user's pre-stored VIN, and sends them to the target charging pile.

[0045] Considering that relying solely on single-dimensional data (such as user demand alone) will lead to grid imbalance or battery damage, this means that in order to ensure that charging behavior is coordinated with grid stability, avoid overload risks, meet personalized charging needs (such as fast charging / slow charging selection) and optimize charging strategies based on vehicle battery characteristics (such as capacity, charging curve), in this embodiment of the application, the operation platform can generate dynamic charging control instructions based on real-time grid load data, user charging needs, and vehicle battery parameters corresponding to the user's pre-stored VIN. As an embodiment of the present application, the operation platform can generate dynamic charging control instructions based on real-time grid load data, user charging needs, and vehicle battery parameters corresponding to the user's pre-stored VIN through steps S1021 to S1024, as detailed below:

[0046] Step S1021: Obtain the historical charging data and battery health status of the vehicle corresponding to the VIN pre-stored by the user.

[0047] Step S1022: Combined with real-time grid load data, the optimal charging power curve is predicted through a reinforcement learning model.

[0048] Specifically, combining real-time grid load data, the optimal charging power curve can be predicted by the reinforcement learning model through steps S10221 to S10224, as detailed below:

[0049] Step S10221: Collect real-time grid load data and perform preprocessing.

[0050] Specifically, real-time grid load data can be obtained from the grid dispatch center interface, including: the current total grid load (unit: MW), the real-time load rate (percentage) of the transformer in the area where the target charging station is located, the grid load forecast for the next hour, and time-of-day electricity prices (such as peak, valley, and flat rates). After collecting this data, it can be normalized, that is, the grid load data is normalized to a range of 0 to 1, for example, the current load as a percentage of the transformer's maximum capacity.

[0051] Step S10222: Construct the core elements of the reinforcement learning model.

[0052] In the implementation of this application, the core elements of constructing a reinforcement learning model include the definition of state space and action space and the design of reward function, wherein the definition of state space includes input features such as grid-side data (for example, real-time load, load rate, future load forecast, current electricity price, etc.), vehicle data (for example, current SOC of battery, maximum allowed charging power, battery health status, etc.) and user needs (for example, expected charging completion time, cost budget priority, etc.); the action space includes adjusting charging power (for example, increasing from 50kW to 80kW, or decreasing to 30kW), recommending delayed charging period (for example, "delaying charging for 1 hour can save 20% of costs") and switching charging mode (fast charging / slow charging), etc.; the reward function includes grid-side rewards, user-side rewards and battery health penalties, etc.

[0053] Step S10223: Model training and optimization.

[0054] It mainly includes offline pre-training and online real-time optimization. Among them, offline pre-training can be performed by inputting a number of historical charging records (for example, 100,000), and then iteratively updating the strategy through the Q-learning algorithm. That is, initially randomly selecting an action, recording the reward value obtained, and updating the Q table (state-action value table) through the Bellman equation, so that the model gradually learns to select high-reward actions under specific grid load conditions; online real-time optimization can be when the model is deployed to the actual system, obtaining the latest grid load data every preset time (for example, 5 minutes). After each charging task is completed, the model parameters are updated according to the actual results (such as whether the grid overload alarm is triggered, user satisfaction score), and then balancing exploration and utilization through the ε-greedy strategy: for example, the current optimal action is selected with a 90% probability, and a new action is randomly tried with a 10% probability.

[0055] Step S10224: Generate optimal charging power curve

[0056] Specifically, it outputs the corresponding candidate strategies based on the current vehicle SOC, user demand, and grid load rate, then calculates the comprehensive score of each strategy. Finally, it selects strategy B with the highest total score and generates the corresponding charging power curve.

[0057] Step S1023: When the predicted power curve conflicts with the user's needs, an adjustment suggestion is sent to the user's mobile terminal.

[0058] Step S1024: Generate a final control instruction based on user feedback or a default strategy.

[0059] Specifically, if the user selects priority charging speed, a temporary power boost exceeding the grid load threshold is permitted. If the user selects economy mode, the charging plan is automatically adjusted to match the off-peak electricity price period. The user-selected mode is superimposed on real-time grid data to generate segmented charging control instructions. The segmented charging control instructions can be executed as follows: During the power boost phase, the total grid load and the load rate of the charging station transformer are monitored in real time. When any of the following conditions are met, the system automatically switches to economy mode: the total grid load exceeds a preset percentage of the regional power supply capacity threshold, such as 90%; or the charging station transformer load rate exceeds a preset percentage, such as 85%, for a preset period of time (e.g., 5 minutes). Key parameters of the mode switching event, such as the switching time, load threshold, and impact range, are generated into a verifiable log and written to the blockchain evidence node.

[0060] As can be seen from step S102 of the above embodiment, control instructions are dynamically generated based on real-time grid load data, user demand, and vehicle battery parameters associated with the user's pre-stored VIN, so that the charging strategy can synchronously respond to changes in grid status and vehicle characteristics, breaking through the limitations of traditional fixed strategies and enhancing grid stability while ensuring charging efficiency.

[0061] Step S103: When the target charging pile executes the control instruction, the battery status parameters of the vehicle battery management system BMS and the charging pile operation data are collected in real time.

[0062] In the embodiment of the present application, the battery status parameters of the vehicle battery management system (BMS) may include the vehicle battery's state of charge (SOC), health status, temperature parameters, electrical parameters (voltage, current, internal resistance, etc.), and fault codes, etc., while the charging pile operation data mainly includes the target charging pile's input / output voltage, current, power, power factor and other electrical parameters, status parameters (for example, charging pile operating mode, cooling system operating status, connection status, etc.), environmental parameters, and fault information, etc. These battery status parameters and charging pile operation data can be obtained through real-time communication between the target charging pile and the vehicle when the target charging pile executes a control command.

[0063] Step S104: Associating the battery status parameters and charging pile operation data with the user's pre-stored VIN, and dynamically adjusting the charging parameters through multi-dimensional data fusion analysis.

[0064] On the one hand, battery status parameters (such as SOC, temperature, and voltage) are core monitoring indicators for charging safety. If they are not associated with the user's pre-stored VIN, it is impossible to distinguish the charging data of different vehicles, and the control strategy may be incorrectly applied. On the other hand, single-dimensional control, such as speed reduction based solely on temperature, may lead to low charging efficiency or safety hazards. Therefore, to ensure clear data ownership, prevent data confusion, and achieve adaptive control of the charging process, in this embodiment of the application, battery status parameters and charging pile operating data can be associated with the user's pre-stored VIN, and charging parameters can be dynamically adjusted through multi-dimensional data fusion analysis.

[0065] As one embodiment of the present application, dynamically adjusting charging parameters through multi-dimensional data fusion analysis can include: establishing a multi-parameter correlation matrix containing battery SOC value, temperature change rate, and voltage fluctuation coefficient; calculating the dynamic weight coefficient of each parameter in the multi-parameter correlation matrix through a sliding time window algorithm; and triggering a charging parameter adjustment strategy based on the distribution of each weight coefficient in the multi-parameter correlation matrix. In the above embodiment, triggering a charging parameter adjustment strategy based on the distribution of each weight coefficient in the multi-parameter correlation matrix can include adjusting the operating mode of the heat dissipation system of the target charging pile according to the temperature change rate; correcting the charging curve smoothness parameter based on the voltage fluctuation coefficient; and recalculating the optimal charging time based on the battery SOC value. After the above charging parameter adjustment strategy is triggered, the target charging station executes as follows: recording the maximum temperature value and voltage fluctuation amplitude during each charging process to construct a time series database; inputting the time series data into a pre-trained LSTM neural network model to output the battery life decay curve prediction result; when the prediction result shows that the remaining life is lower than a preset proportion of the rated value, generating customized maintenance suggestions and pushing them to the user's mobile terminal.

[0066] Furthermore, it also includes abnormal handling of the charging process, that is, when the temperature change rate continues to exceed the safety threshold, the following operations are performed: prompting the user to check the battery status through the display screen of the target charging pile; pushing alternative charging station information to the user's mobile terminal; terminating the current charging and generating a settlement message containing the temperature abnormality record; wherein, pushing alternative charging station information to the user's mobile terminal can be: based on the user's current location coordinates and real-time road conditions data, calculating the optimal driving route to each alternative charging station; according to the end coordinates of the optimal path, obtaining the real-time number of idle piles and the estimated charging cost; dynamically rendering the comprehensive recommendation index and estimated total time of each alternative station on the map interface of the user's mobile terminal, that is: the comprehensive recommendation index of each alternative charging station calculated based on the weighted calculation of the path duration, electricity price, and number of idle piles, the navigation guidance and key node prompts of the optimal path, and the estimated total time of each charging station, that is, driving time + charging waiting time + charging time.

[0067] From the above embodiment, it can be seen that by correlating and analyzing the real-time operating data collected by the target charging pile with the user's pre-stored VIN, a dynamic mapping relationship of identity-state-control is established, and closed-loop optimization and adjustment of charging parameters are achieved, providing data support for solving safety hazards such as battery overheating and voltage abnormalities.

[0068] Step S105: After charging is completed, an encrypted settlement message is generated based on the charging record associated with the user's pre-stored VIN.

[0069] Considering that if the charging record is not associated with the user's pre-stored VIN, the corresponding relationship between the charging behavior and the vehicle cannot be traced, and there is no basis for dispute resolution. Therefore, in order to ensure billing accuracy, for example, to prevent "mistaking the correct charge" type of billing errors, in an embodiment of the present application, after charging is completed, an encrypted settlement message can be generated based on the charging record associated with the user's pre-stored VIN. Specifically, it can be: extracting the user's pre-stored VIN, charging start and end time, and actual charging amount data; using the user's private key bound to the user's pre-stored VIN to digitally sign the actual charging amount data; and encrypting the signed actual charging amount data with the charging pile identity information to generate a settlement message.

[0070] The above embodiment is an online settlement mode, that is, the target charging pile and the operation platform can communicate normally. In the actual application scenario of the present application, it also includes an offline settlement mode, that is, when the network is interrupted, the target charging pile uses a preset offline key to encrypt the settlement data; generates a temporary credential containing the hash value of the VIN and a timestamp; after the network is restored, the operation platform verifies the integrity of the temporary credential and the offline data. If the verification is successful, the charging settlement is completed. In the above embodiment, the operation platform verifies the integrity of the temporary credential and the offline data by: comparing the hash value of the VIN in the temporary credential with the hash value of the user's pre-stored VIN; if the verification is successful, verify whether the timestamp in the temporary credential is within the validity period of the charging task; if the verification is successful, confirm the legitimacy of the offline key through the charging pile digital certificate, including: verifying whether the certificate issuing authority is in the platform whitelist and checking whether the certificate validity period covers the charging time period; if the charging pile digital certificate confirms that the legitimacy of the offline key has passed, the integrity verification of the temporary credential and the offline data is considered to have passed.

[0071] Step S106: The encrypted settlement message is stored on the chain through blockchain technology, and the user is notified after the fee settlement is completed.

[0072] It is well known that centralized storage is vulnerable to data tampering attacks, while blockchain evidence storage can avoid the risk of single point failure. Therefore, in order to solve the problems of "data authenticity" and "settlement traceability", blockchain technology can be used to store encrypted settlement messages on the chain, and users can be notified after the fee settlement is completed.

[0073] As can be seen from steps S105 and S106 of the above embodiment, blockchain technology is used to store charging records associated with VINs on the chain, and its decentralized and tamper-proof characteristics are utilized to ensure the integrity and auditability of settlement data, effectively avoiding the data leakage and single point failure risks of traditional centralized settlement systems.

[0074] From the above attached Figure 1As can be seen from the example of a charging operation method based on a vehicle identification code, on the one hand, by bidirectionally binding and verifying the VIN entered by the user with the vehicle hardware information obtained in real time by the charging pile, a dual-channel authentication mechanism is established, which effectively prevents illegal users from accessing the charging system by forging account information, thereby fundamentally improving the security of charging operations. Control instructions are dynamically generated based on real-time grid load data, user demand, and pre-stored vehicle battery parameters associated with the VIN, enabling the charging strategy to synchronously respond to changes in grid status and vehicle characteristics, breaking through the limitations of traditional fixed strategies and enhancing grid stability while ensuring charging efficiency. On the other hand, by correlating and analyzing the real-time operating data collected by the charging pile with the pre-stored VIN, a dynamic mapping relationship between identity, status, and control is established, achieving closed-loop optimization and adjustment of charging parameters, providing data support for resolving safety hazards such as battery overheating and voltage anomalies. Thirdly, blockchain technology is used to store VIN-related charging records on-chain, leveraging its decentralized and tamper-proof characteristics to ensure the integrity and auditability of settlement data, effectively avoiding the data leakage and single point failure risks of traditional centralized settlement systems. In summary, the technical solution of the present application can significantly improve the charging safety of charging piles, optimize efficiency and ensure cost credibility.

[0075] Please see the attached Figure 2 , is a charging operation device based on a vehicle identification code provided in an embodiment of the present application. The device may include a binding module 201, a first generation module 202, a collection module 203, an association module 204, a second generation module 205, and an evidence storage module 206, which are described in detail as follows:

[0076] Binding module 201 is used to establish a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identification code (VIN) and license plate number input by the user, and store the bound VIN as the user's pre-stored VIN in the database of the operation platform;

[0077] The first generation module 202 is used for the operation platform to generate dynamic charging control instructions based on real-time grid load data, user charging requirements, and vehicle battery parameters corresponding to the user's pre-stored VIN and send them to the target charging pile;

[0078] The acquisition module 203 is used to collect the battery status parameters of the vehicle battery management system BMS and the charging pile operation data in real time when the target charging pile executes the control instruction;

[0079] An association module 204 is used to associate battery status parameters and charging pile operation data with the user's pre-stored VIN, and dynamically adjust charging parameters through multi-dimensional data fusion analysis;

[0080] The second generating module 205 is configured to generate an encrypted settlement message based on the charging record associated with the user's pre-stored VIN after charging is completed;

[0081] The evidence storage module 206 is used to store the encrypted settlement message on the chain through blockchain technology and notify the user after the fee settlement is completed.

[0082] From the above attached Figure 2 From the example of a charging operation device based on a vehicle identification code, it can be seen that, on the one hand, the dynamic scheduling engine integrates the grid time-sharing load data and the charging pile group status data in real time, and combines the multi-objective optimization algorithm to generate the charging queue sorting, so that the charging task allocation can dynamically adapt to the grid carrying capacity and equipment operating status, effectively balancing the grid load and avoiding the risk of local overload. At the same time, by optimizing the spatiotemporal resource allocation of charging piles, the utilization rate of charging piles is significantly improved; on the other hand, during the charging process, through the real-time collection and abnormal pattern recognition of multi-dimensional operation data, the power redistribution strategy can be quickly triggered, the power supply parameters of adjacent charging piles can be dynamically adjusted, the fault impact can be isolated in time and the continuity of charging service can be maintained, thereby ensuring the safety of the charging process and the overall reliability of the system; thirdly, an encrypted communication link is used to realize secure data transmission between the charging pile monitoring node and the cloud platform, and the key parameters of the charging process are distributedly stored in combination with blockchain smart contracts, which not only prevents the risk of data tampering during transmission and storage, but also improves the transparency and credibility of the billing process through a multi-party verification mechanism, reducing user disputes.

[0083] Figure 3 Schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Figure 3 As shown, the electronic device 3 of this embodiment mainly includes: a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30, such as a program for a charging operation method based on a vehicle identification code. When the processor 30 executes the computer program 32, the steps in the embodiment of the charging operation method based on a vehicle identification code are implemented, such as Figure 1 Alternatively, when the processor 30 executes the computer program 32, the functions of the modules / units in the above-mentioned device embodiments are realized, for example Figure 2 The functions of the binding module 201, the first generation module 202, the collection module 203, the association module 204, the second generation module 205 and the evidence storage module 206 are shown.

[0084] For example, a computer program 32 for a vehicle identification code (VIN)-based charging operation method primarily includes: establishing a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identification code (VIN) and license plate number input by the user, and storing the bound VIN as the user's pre-stored VIN in the operation platform's database; generating dynamic charging control instructions based on real-time grid load data, user charging demand, and vehicle battery parameters corresponding to the user's pre-stored VIN, and issuing them to the target charging pile; collecting battery status parameters and charging pile operation data from the vehicle's battery management system (BMS) in real time when the target charging pile executes the control instructions; associating the battery status parameters and charging pile operation data with the user's pre-stored VIN, and dynamically adjusting charging parameters through multi-dimensional data fusion analysis; generating an encrypted settlement message based on the charging record associated with the user's pre-stored VIN after charging is completed; and storing the encrypted settlement message on-chain using blockchain technology, and notifying the user after the fee settlement is completed. The computer program 32 can be divided into one or more modules / units, one or more of which are stored in the memory 31 and executed by the processor 30 to complete the present application. One or more modules / units may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program 32 in the electronic device 3. For example, the computer program 32 may be divided into the functions of a binding module 201, a first generation module 202, a collection module 203, an association module 204, a second generation module 205, and a storage module 206 (modules in the virtual device). The specific functions of each module are as follows: the binding module 201 is used to establish a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identity identification code VIN and license plate number input by the user, and store the bound VIN as the user's pre-stored VIN in the database of the operation platform; the first generation module 202 is used for the operation platform to establish a binding relationship between the vehicle corresponding to the VIN and the operation platform based on real-time grid load data, user charging needs, and the vehicle battery corresponding to the user's pre-stored VIN. parameters, generate dynamic charging control instructions and send them to the target charging pile; the acquisition module 203 is used to collect the battery status parameters and charging pile operation data of the vehicle battery management system BMS and the charging pile operation data in real time when the target charging pile executes the control instructions; the association module 204 is used to associate the battery status parameters and charging pile operation data with the user's pre-stored VIN, and dynamically adjust the charging parameters through multi-dimensional data fusion analysis; the second generation module 205 is used to generate an encrypted settlement message based on the charging record associated with the user's pre-stored VIN after charging is completed; the evidence storage module 206 is used to store the encrypted settlement message on the chain through blockchain technology, and notify the user after the fee settlement is completed.

[0085] The electronic device 3 may include but is not limited to a processor 30 and a memory 31. Those skilled in the art will appreciate that Figure 3It is only an example of electronic device 3 and does not constitute a limitation of electronic device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0086] The processor 30 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0087] The memory 31 can be an internal storage unit of the electronic device 3, such as the hard drive or memory of the electronic device 3. The memory 31 can also be an external storage device of the electronic device 3, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Furthermore, the memory 31 can include both the internal storage unit of the electronic device 3 and an external storage device. The memory 31 is used to store computer programs and other programs and data required by the electronic device. The memory 31 can also be used to temporarily store data that has been output or is about to be output.

[0088] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned device can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0089] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0090] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0091] In the embodiments provided in this application, it should be understood that the disclosed devices / equipment and methods can be implemented in other ways. For example, the device / equipment embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0092] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0093] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0094] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and a computer program can also be used to instruct related hardware to complete the process. The computer program of the charging operation method based on the vehicle identification code can be stored in a storage medium. When the computer program is executed by the processor, it can implement the steps of each of the above-mentioned method embodiments, namely, by obtaining the vehicle identity identification code (VIN) and license plate number input by the user, a binding relationship between the vehicle corresponding to the VIN and the operation platform is established, and the bound VIN is stored as the user's pre-stored VIN in the database of the operation platform; the operation platform generates dynamic charging control instructions based on real-time grid load data, user charging demand, and vehicle battery parameters corresponding to the user's pre-stored VIN, and sends them to the target charging pile; when the target charging pile executes the control instruction, the battery status parameters and charging pile operation data of the vehicle battery management system (BMS) are collected in real time; the battery status parameters and charging pile operation data are associated with the user's pre-stored VIN, and the charging parameters are dynamically adjusted through multi-dimensional data fusion analysis; after charging is completed, an encrypted settlement message is generated based on the charging record associated with the user's pre-stored VIN; the encrypted settlement message is stored on the chain through blockchain technology, and the user is notified after the fee settlement is completed. Computer programs include computer program code, which may be in source code, object code, executable files, or some intermediate form. Storage media may include any entity or device capable of carrying computer program code, recording media, USB flash drives, removable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signals, telecommunications signals, and software distribution media. It should be noted that the content of storage media may be appropriately expanded or reduced based on the requirements of legislation and patent practice within a jurisdiction. For example, in some jurisdictions, based on legislation and patent practice, storage media do not include electric carrier signals or telecommunications signals.

[0095] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application. The specific implementation methods described above further explain the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above description is only the specific implementation method of the present application and is not used to limit the protection scope of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included in the protection scope of the present invention.

Claims

1. A charging operation method based on vehicle identification code, characterized in that: The method comprises: The binding relationship between the vehicle corresponding to the VIN and the operation platform is established by obtaining the vehicle identification code VIN and license plate number input by the user, and the bound VIN is stored as the user's pre-stored VIN in the database of the operation platform. The establishment of the binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identification code VIN and license plate number input by the user includes: when the charging gun of the target charging pile is inserted into the vehicle corresponding to the VIN, the VIN is obtained in real time by collecting the interface of the vehicle battery management system BMS; when the vehicle BMS communication is abnormal, the RFID card reader is activated to scan the vehicle electronic tag to obtain the backup VIN; the VIN obtained in real time or the backup VIN is matched and verified with the user's pre-stored VIN The matching and verification of the VIN or the backup VIN obtained in real time with the VIN code pre-stored by the user includes: the operation platform generates a dynamic verification key and divides it into a first key segment and a second key segment; sends the first key segment to the mobile terminal of the user for biometric verification; transmits the second key segment to the target charging pile, and controls its display screen to generate a dynamic QR code containing the second key segment; after the user scans the dynamic QR code, the scanning result is correlated with the result of the biometric verification; when the verification passes and the VIN or the backup VIN obtained in real time is consistent with the VIN pre-stored by the user, the matching and verification of the VIN or the backup VIN obtained in real time with the VIN pre-stored by the user is passed; The operation platform generates dynamic charging control instructions based on real-time grid load data, user charging requirements, and vehicle battery parameters corresponding to the user's pre-stored VIN and sends them to the target charging pile; When the target charging pile executes the control instruction, the battery status parameters of the vehicle BMS and the charging pile operation data are collected in real time; Associating the battery status parameters and charging pile operation data with the user's pre-stored VIN, and dynamically adjusting the charging parameters through multi-dimensional data fusion analysis; dynamically adjusting the charging parameters through multi-dimensional data fusion analysis includes: establishing a multi-parameter correlation matrix including battery SOC value, temperature change rate, and voltage fluctuation coefficient; calculating dynamic weight coefficients of each parameter in the multi-parameter correlation matrix through a sliding time window algorithm; and triggering a charging parameter adjustment strategy based on the dynamic weight coefficient distribution; After charging is completed, an encrypted settlement message is generated based on the charging record associated with the user's pre-stored VIN; The encrypted settlement message is stored on the chain through blockchain technology, and the user is notified after the fee settlement is completed.

2. The charging operation method based on the vehicle identification code according to claim 1, characterized in that: The operation platform generates dynamic charging control instructions based on real-time grid load data, user charging requirements, and vehicle battery parameters corresponding to the user's pre-stored VIN, including: Obtain the historical charging data and battery health status of the vehicle corresponding to the VIN pre-stored by the user; In combination with the real-time grid load data, an optimal charging power curve is predicted through a reinforcement learning model; When the predicted power curve conflicts with the user's needs, sending an adjustment suggestion to the user's mobile terminal; A final control instruction is generated according to the user feedback or a default strategy.

3. The charging operation method based on the vehicle identification code according to claim 2, characterized in that: The execution of the charging parameter adjustment strategy includes: Record the maximum temperature value and voltage fluctuation amplitude during each charging process and build a time series database; Inputting the time series data into a pre-trained LSTM neural network model and outputting a battery life attenuation curve prediction result; When the prediction result shows that the remaining life is lower than a preset proportion of the rated value, a customized maintenance suggestion is generated and pushed to the user's mobile terminal.

4. The charging operation method based on the vehicle identification code according to claim 1, characterized in that: The generating of an encrypted settlement message based on the charging record associated with the user's pre-stored VIN includes: Extract the user's pre-stored VIN, charging start and end time, and actual charging amount data; Digitally signing the actual charge amount data using a user private key bound to the user's pre-stored VIN; The signed actual charging amount data and the charging pile identity information are encrypted together to generate a settlement message.

5. A charging operation device based on a vehicle identification code, characterized in that: The device comprises: The binding module is used to establish a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identification code VIN and license plate number input by the user, and store the bound VIN as the user's pre-stored VIN in the database of the operation platform. The establishment of a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identification code VIN and license plate number input by the user includes: when the charging gun of the target charging pile is inserted into the vehicle corresponding to the VIN, the VIN is obtained in real time by collecting the interface of the vehicle battery management system BMS; when the vehicle BMS communication is abnormal, the RFID reader is activated to scan the vehicle electronic tag to obtain the backup VIN; the VIN obtained in real time or the backup VIN is compared with the user's pre-stored VIN Perform matching verification; the matching verification of the VIN or the backup VIN obtained in real time with the VIN code pre-stored by the user includes: the operation platform generates a dynamic verification key and divides it into a first key segment and a second key segment; sends the first key segment to the user's mobile terminal for biometric verification; transmits the second key segment to the target charging pile, and controls its display screen to generate a dynamic QR code containing the second key segment; after the user scans the dynamic QR code, the scanning result is associated with the result of the biometric verification for verification; when the verification passes and the VIN or the backup VIN obtained in real time is consistent with the VIN pre-stored by the user, the matching verification of the VIN or the backup VIN obtained in real time with the VIN pre-stored by the user is passed; The first generation module is used for the operation platform to generate dynamic charging control instructions based on real-time grid load data, user charging needs and vehicle battery parameters corresponding to the user's pre-stored VIN and send them to the target charging pile; An acquisition module, configured to acquire battery status parameters of the vehicle's BMS and charging pile operation data in real time when the target charging pile executes a control instruction; An association module is configured to associate the battery status parameters and charging pile operation data with the user's pre-stored VIN, and dynamically adjust the charging parameters through multi-dimensional data fusion analysis; the dynamic adjustment of the charging parameters through multi-dimensional data fusion analysis includes: establishing a multi-parameter association matrix including the battery SOC value, temperature change rate, and voltage fluctuation coefficient; calculating the dynamic weight coefficient of each parameter in the multi-parameter association matrix through a sliding time window algorithm; and triggering a charging parameter adjustment strategy based on the dynamic weight coefficient distribution; A second generating module is configured to generate an encrypted settlement message based on the charging record associated with the user's pre-stored VIN after charging is completed; The evidence storage module is used to store the encrypted settlement message on the chain through blockchain technology and notify the user after the fee settlement is completed.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

7. A storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

Images